The Hierarchical Iterative Identification Algorithm for Multi-Input-Output-Error Systems with Autoregressive Noise

被引：41
|
作者：
Ding, Jiling [1 ]
机构：
[1] Jining Univ, Dept Math, Qufu 273155, Peoples R China
来源：
COMPLEXITY | 2017年
关键词：
PARAMETER-ESTIMATION; LEAST-SQUARES; STATE; DESIGN;
D O I：
10.1155/2017/5292894
中图分类号：
O1 [数学];
学科分类号：
0701 ; 070101 ;
摘要：
This paper considers the identification problem of multi-input-output-error autoregressive systems. A hierarchical gradient based iterative (H-GI) algorithm and a hierarchical least squares based iterative (H-LSI) algorithm are presented by using the hierarchical identification principle. A gradient based iterative (GI) algorithm and a least squares based iterative (LSI) algorithm are presented for comparison. The simulation results indicate that the H-LSI algorithm can obtain more accurate parameter estimates than the LSI algorithm, and the H-GI algorithm converges faster than the GI algorithm.
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页数：11
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